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Asset Tag: bioinformatics

September 22, 2019

Novel molecules lncRNAs, tRFs and circRNAs deciphered from next-generation sequencing/RNA sequencing: computational databases and tools.

Powerful next-generation sequencing (NGS) technologies, more specifically RNA sequencing (RNA-seq), have been pivotal toward the detection and analysis and hypotheses generation of novel biomolecules, long noncoding RNAs (lncRNAs), tRNA-derived fragments (tRFs) and circular RNAs (circRNAs). Experimental validation of the occurrence of these biomolecules inside the cell has been reported. Their differential expression and functionally important role in several cancers types as well as other diseases such as Alzheimer’s and cardiovascular diseases have garnered interest toward further studies in this research arena. In this review, starting from a brief relevant introduction to NGS and RNA-seq and the expression and role of lncRNAs, tRFs and circRNAs in cancer, we have comprehensively analyzed the current landscape of databases developed and computational software used for analyses and visualization for this emerging and highly interesting field of these novel biomolecules. Our review will help the end users and research investigators gain information on the existing databases and tools as well as an understanding of the specific features which these offer. This will be useful for the researchers in their proper usage thereby guiding them toward novel hypotheses generation and saving time and costs involved in extensive experimental processes in these three different novel functional RNAs.© The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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September 22, 2019

A survey of the sorghum transcriptome using single-molecule long reads.

Alternative splicing and alternative polyadenylation (APA) of pre-mRNAs greatly contribute to transcriptome diversity, coding capacity of a genome and gene regulatory mechanisms in eukaryotes. Second-generation sequencing technologies have been extensively used to analyse transcriptomes. However, a major limitation of short-read data is that it is difficult to accurately predict full-length splice isoforms. Here we sequenced the sorghum transcriptome using Pacific Biosciences single-molecule real-time long-read isoform sequencing and developed a pipeline called TAPIS (Transcriptome Analysis Pipeline for Isoform Sequencing) to identify full-length splice isoforms and APA sites. Our analysis reveals transcriptome-wide full-length isoforms at an unprecedented scale with over 11,000 novel splice isoforms. Additionally, we uncover APA of ~11,000 expressed genes and more than 2,100 novel genes. These results greatly enhance sorghum gene annotations and aid in studying gene regulation in this important bioenergy crop. The TAPIS pipeline will serve as a useful tool to analyse Iso-Seq data from any organism.

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September 22, 2019

CSSSCL: a python package that uses combined sequence similarity scores for accurate taxonomic classification of long and short sequence reads.

Sequence comparison of genetic material between known and unknown organisms plays a crucial role in genomics, metagenomics and phylogenetic analysis. The emerging long-read sequencing technologies can now produce reads of tens of kilobases in length that promise a more accurate assessment of their origin. To facilitate the classification of long and short DNA sequences, we have developed a Python package that implements a new sequence classification model that we have demonstrated to improve the classification accuracy when compared with other state of the art classification methods. For the purpose of validation, and to demonstrate its usefulness, we test the combined sequence similarity score classifier (CSSSCL) using three different datasets, including a metagenomic dataset composed of short reads.Package’s source code and test datasets are available under the GPLv3 license at https://github.com/oicr-ibc/cssscl.ivan.borozan@oicr.on.caSupplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

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September 22, 2019

MUMmer4: A fast and versatile genome alignment system.

The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads to a reference genome, and comparing different assemblies of the same genome. Despite its broad utility, MUMmer3 has limitations that can make it difficult to use for large genomes and for the very large sequence data sets that are common today. In this paper we describe MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the nucmer program in MUMmer4 is easily able to handle alignments of large genomes; we illustrate this with an alignment of the human and chimpanzee genomes, which allows us to compute that the two species are 98% identical across 96% of their length. With the enhancements described here, MUMmer4 can also be used to efficiently align reads to reference genomes, although it is less sensitive and accurate than the dedicated read aligners. The nucmer aligner in MUMmer4 can now be called from scripting languages such as Perl, Python and Ruby. These improvements make MUMer4 one the most versatile genome alignment packages available.

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September 22, 2019

SimulaTE: simulating complex landscapes of transposable elements of populations.

Motivation Estimating the abundance of transposable elements (TEs) in populations (or tissues) promises to answer many open research questions. However, progress is hampered by the lack of concordance between different approaches for TE identification and thus potentially unreliable results. Results To address this problem, we developed SimulaTE a tool that generates TE landscapes for populations using a newly developed domain specific language (DSL). The simple syntax of our DSL allows for easily building even complex TE landscapes that have, for example, nested, truncated and highly diverged TE insertions. Reads may be simulated for the populations using different sequencing technologies (PacBio, Illumina paired-ends) and strategies (sequencing individuals and pooled populations). The comparison between the expected (i.e. simulated) and the observed results will guide researchers in finding the most suitable approach for a particular research question. Availability and implementation SimulaTE is implemented in Python and available at https://sourceforge.net/projects/simulates/. Manual https://sourceforge.net/p/simulates/wiki/Home/#manual; Test data and tutorials https://sourceforge.net/p/simulates/wiki/Home/#walkthrough; Validation https://sourceforge.net/p/simulates/wiki/Home/#validation. Contact robert.kofler@vetmeduni.ac.at

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September 22, 2019

Redkmer: An Assembly-Free Pipeline for the Identification of Abundant and Specific X-Chromosome Target Sequences for X-Shredding by CRISPR Endonucleases.

CRISPR-based synthetic sex ratio distorters, which operate by shredding the X-chromosome during male meiosis, are promising tools for the area-wide control of harmful insect pest or disease vector species. X-shredders have been proposed as tools to suppress insect populations by biasing the sex ratio of the wild population toward males, thus reducing its natural reproductive potential. However, to build synthetic X-shredders based on CRISPR, the selection of gRNA targets, in the form of high-copy sequence repeats on the X chromosome of a given species, is difficult, since such repeats are not accurately resolved in genome assemblies and cannot be assigned to chromosomes with confidence. We have therefore developed the redkmer computational pipeline, designed to identify short and highly abundant sequence elements occurring uniquely on the X chromosome. Redkmer was designed to use as input minimally processed whole genome sequence data from males and females. We tested redkmer with short- and long-read whole genome sequence data of Anopheles gambiae, the major vector of human malaria, in which the X-shredding paradigm was originally developed. Redkmer established long reads as chromosomal proxies with excellent correlation to the genome assembly and used them to rank X-candidate kmers for their level of X-specificity and abundance. Among these, a high-confidence set of 25-mers was identified, many belonging to previously known X-chromosome repeats of Anopheles gambiae, including the ribosomal gene array and the selfish elements harbored within it. Data from a control strain, in which these repeats are shared with the Y chromosome, confirmed the elimination of these kmers during filtering. Finally, we show that redkmer output can be linked directly to gRNA selection and off-target prediction. In addition, the output of redkmer, including the prediction of chromosomal origin of single-molecule long reads and chromosome specific kmers, could also be used for the characterization of other biologically relevant sex chromosome sequences, a task that is frequently hampered by the repetitiveness of sex chromosome sequence content.

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September 22, 2019

LTR_retriever: A highly accurate and sensitive program for identification of long terminal repeat retrotransposons.

Long terminal repeat retrotransposons (LTR-RTs) are prevalent in plant genomes. The identification of LTR-RTs is critical for achieving high-quality gene annotation. Based on the well-conserved structure, multiple programs were developed for the de novo identification of LTR-RTs; however, these programs are associated with low specificity and high false discovery rates. Here, we report LTR_retriever, a multithreading-empowered Perl program that identifies LTR-RTs and generates high-quality LTR libraries from genomic sequences. LTR_retriever demonstrated significant improvements by achieving high levels of sensitivity (91%), specificity (97%), accuracy (96%), and precision (90%) in rice (Oryza sativa). LTR_retriever is also compatible with long sequencing reads. With 40k self-corrected PacBio reads equivalent to 4.5× genome coverage in Arabidopsis (Arabidopsis thaliana), the constructed LTR library showed excellent sensitivity and specificity. In addition to canonical LTR-RTs with 5′-TG…CA-3′ termini, LTR_retriever also identifies noncanonical LTR-RTs (non-TGCA), which have been largely ignored in genome-wide studies. We identified seven types of noncanonical LTRs from 42 out of 50 plant genomes. The majority of noncanonical LTRs areCopiaelements, with which the LTR is four times shorter than that of otherCopiaelements, which may be a result of their target specificity. Strikingly, non-TGCACopiaelements are often located in genic regions and preferentially insert nearby or within genes, indicating their impact on the evolution of genes and their potential as mutagenesis tools.© 2018 American Society of Plant Biologists. All Rights Reserved.

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September 22, 2019

Jointly aligning a group of DNA reads improves accuracy of identifying large deletions.

Performing sequence alignment to identify structural variants, such as large deletions, from genome sequencing data is a fundamental task, but current methods are far from perfect. The current practice is to independently align each DNA read to a reference genome. We show that the propensity of genomic rearrangements to accumulate in repeat-rich regions imposes severe ambiguities in these alignments, and consequently on the variant calls-with current read lengths, this affects more than one third of known large deletions in the C. Venter genome. We present a method to jointly align reads to a genome, whereby alignment ambiguity of one read can be disambiguated by other reads. We show this leads to a significant improvement in the accuracy of identifying large deletions (=20 bases), while imposing minimal computational overhead and maintaining an overall running time that is at par with current tools. A software implementation is available as an open-source Python program called JRA at https://bitbucket.org/jointreadalignment/jra-src.

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September 22, 2019

Simulating the dynamics of targeted capture sequencing with CapSim.

Targeted sequencing using capture probes has become increasingly popular in clinical applications due to its scalability and cost-effectiveness. The approach also allows for higher sequencing coverage of the targeted regions resulting in better analysis statistical power. However, because of the dynamics of the hybridization process, it is difficult to evaluate the efficiency of the probe design prior to the experiments which are time consuming and costly.We developed CapSim, a software package for simulation of targeted sequencing. Given a genome sequence and a set of probes, CapSim simulates the fragmentation, the dynamics of probe hybridization and the sequencing of the captured fragments on Illumina and PacBio sequencing platforms. The simulated data can be used for evaluating the performance of the analysis pipeline, as well as the efficiency of the probe design. Parameters of the various stages in the sequencing process can also be evaluated in order to optimize the experiments.CapSim is publicly available under BSD license at https://github.com/Devika1/capsim.l.coin@imb.uq.edu.au.Supplementary data are available at Bioinformatics online.© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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September 22, 2019

Conventional and single-molecule targeted sequencing method for specific variant detection in IKBKG while bypassing the IKBKGP1 pseudogene.

In addition to Sanger sequencing, next-generation sequencing of gene panels and exomes has emerged as a standard diagnostic tool in many laboratories. However, these captures can miss regions, have poor efficiency, or capture pseudogenes, which hamper proper diagnoses. One such example is the primary immunodeficiency-associated gene IKBKG. Its pseudogene IKBKGP1 makes traditional capture methods aspecific. We therefore developed a long-range PCR method to efficiently target IKBKG, as well as two associated genes (IRAK4 and MYD88), while bypassing the IKBKGP1 pseudogene. Sequencing accuracy was evaluated using both conventional short-read technology and a newer long-read, single-molecule sequencer. Different mapping and variant calling options were evaluated in their capability to bypass the pseudogene using both sequencing platforms. Based on these evaluations, we determined a robust diagnostic application for unambiguous sequencing and variant calling in IKBKG, IRAK4, and MYD88. This method allows rapid identification of selected primary immunodeficiency diseases in patients suffering from life-threatening invasive pyogenic bacterial infections. Copyright © 2018 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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September 22, 2019

CliqueSNV: Scalable reconstruction of intra-host viral populations from NGS reads

Highly mutable RNA viruses such as influenza A virus, human immunodeficiency virus and hepatitis C virus exist in infected hosts as highly heterogeneous populations of closely related genomic variants. The presence of low-frequency variants with few mutations with respect to major strains may result in an immune escape, emergence of drug resistance, and an increase of virulence and infectivity. Next-generation sequencing technologies permit detection of sample intra-host viral population at extremely great depth, thus providing an opportunity to access low-frequency variants. Long read lengths offered by single-molecule sequencing technologies allow all viral variants to be sequenced in a single pass. However, high sequencing error rates limit the ability to study heterogeneous viral populations composed of rare, closely related variants. In this article, we present CliqueSNV, a novel reference-based method for reconstruction of viral variants from NGS data. It efficiently constructs an allele graph based on linkage between single nucleotide variations and identifies true viral variants by merging cliques of that graph using combinatorial optimization techniques. The new method outperforms existing methods in both accuracy and running time on experimental and simulated NGS data for titrated levels of known viral variants. For PacBio reads, it accurately reconstructs variants with frequency as low as 0.1%. For Illumina reads, it fully reconstructs main variants. The open source implementation of CliqueSNV is freely available for download at https://github.com/vyacheslav-tsivina/CliqueSNV

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September 22, 2019

Comparison of phasing strategies for whole human genomes.

Humans are a diploid species that inherit one set of chromosomes paternally and one homologous set of chromosomes maternally. Unfortunately, most human sequencing initiatives ignore this fact in that they do not directly delineate the nucleotide content of the maternal and paternal copies of the 23 chromosomes individuals possess (i.e., they do not ‘phase’ the genome) often because of the costs and complexities of doing so. We compared 11 different widely-used approaches to phasing human genomes using the publicly available ‘Genome-In-A-Bottle’ (GIAB) phased version of the NA12878 genome as a gold standard. The phasing strategies we compared included laboratory-based assays that prepare DNA in unique ways to facilitate phasing as well as purely computational approaches that seek to reconstruct phase information from general sequencing reads and constructs or population-level haplotype frequency information obtained through a reference panel of haplotypes. To assess the performance of the 11 approaches, we used metrics that included, among others, switch error rates, haplotype block lengths, the proportion of fully phase-resolved genes, phasing accuracy and yield between pairs of SNVs. Our comparisons suggest that a hybrid or combined approach that leverages: 1. population-based phasing using the SHAPEIT software suite, 2. either genome-wide sequencing read data or parental genotypes, and 3. a large reference panel of variant and haplotype frequencies, provides a fast and efficient way to produce highly accurate phase-resolved individual human genomes. We found that for population-based approaches, phasing performance is enhanced with the addition of genome-wide read data; e.g., whole genome shotgun and/or RNA sequencing reads. Further, we found that the inclusion of parental genotype data within a population-based phasing strategy can provide as much as a ten-fold reduction in phasing errors. We also considered a majority voting scheme for the construction of a consensus haplotype combining multiple predictions for enhanced performance and site coverage. Finally, we also identified DNA sequence signatures associated with the genomic regions harboring phasing switch errors, which included regions of low polymorphism or SNV density.

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September 22, 2019

IMSindel: An accurate intermediate-size indel detection tool incorporating de novo assembly and gapped global-local alignment with split read analysis.

Insertions and deletions (indels) have been implicated in dozens of human diseases through the radical alteration of gene function by short frameshift indels as well as long indels. However, the accurate detection of these indels from next-generation sequencing data is still challenging. This is particularly true for intermediate-size indels (=50?bp), due to the short DNA sequencing reads. Here, we developed a new method that predicts intermediate-size indels using BWA soft-clipped fragments (unmatched fragments in partially mapped reads) and unmapped reads. We report the performance comparison of our method, GATK, PINDEL and ScanIndel, using whole exome sequencing data from the same samples. False positive and false negative counts were determined through Sanger sequencing of all predicted indels across these four methods. The harmonic mean of the recall and precision, F-measure, was used to measure the performance of each method. Our method achieved the highest F-measure of 0.84 in one sample, compared to 0.56 for GATK, 0.52 for PINDEL and 0.46 for ScanIndel. Similar results were obtained in additional samples, demonstrating that our method was superior to the other methods for detecting intermediate-size indels. We believe that this methodology will contribute to the discovery of intermediate-size indels associated with human disease.

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September 22, 2019

SvABA: genome-wide detection of structural variants and indels by local assembly.

Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA’s performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs and substantially improves detection performance for variants in the 20-300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (<1000 bp) templated-sequence insertions copied from distant genomic regions. We applied SvABA to 344 cancer genomes from 11 cancer types and found that short templated-sequence insertions occur in ~4% of all somatic rearrangements. Finally, we demonstrate that SvABA can identify sites of viral integration and cancer driver alterations containing medium-sized (50-300 bp) SVs.© 2018 Wala et al.; Published by Cold Spring Harbor Laboratory Press.

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September 22, 2019

Discovery of gorilla MHC-C expressing C1 ligand for KIR.

In comparison to humans and chimpanzees, gorillas show low diversity at MHC class I genes (Gogo), as reflected by an overall reduced level of allelic variation as well as the absence of a functionally important sequence motif that interacts with killer cell immunoglobulin-like receptors (KIR). Here, we use recently generated large-scale genomic sequence data for a reassessment of allelic diversity at Gogo-C, the gorilla orthologue of HLA-C. Through the combination of long-range amplifications and long-read sequencing technology, we obtained, among the 35 gorillas reanalyzed, three novel full-length genomic sequences including a coding region sequence that has not been previously described. The newly identified Gogo-C*03:01 allele has a divergent recombinant structure that sets it apart from other Gogo-C alleles. Domain-by-domain phylogenetic analysis shows that Gogo-C*03:01 has segments in common with Gogo-B*07, the additional B-like gene that is present on some gorilla MHC haplotypes. Identified in ~ 50% of the gorillas analyzed, the Gogo-C*03:01 allele exclusively encodes the C1 epitope among Gogo-C allotypes, indicating its important function in controlling natural killer cell (NK cell) responses via KIR. We further explored the hypothesis whether gorillas experienced a selective sweep which may have resulted in a general reduction of the gorilla MHC class I repertoire. Our results provide little support for a selective sweep but rather suggest that the overall low Gogo class I diversity can be best explained by drastic demographic changes gorillas experienced in the ancient and recent past.

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